Constructing a molecular subtype model of colon cancer using machine learning.

ABSTRACT: Background: Colon cancer (CRC) is one of the malignant tumors with a high incidence in the world. Many previous studies on CRC have focused on clinical research. With the in-depth study of CRC, the role of molecular mechanisms in CRC has become increasingly important. Currently, machine learning is widely used in medicine. By combining machine learning with molecular mechanisms, we can better understand CRC's pathogenesis and develop new treatments for it. Methods and materials: We used the R language to construct molecular subtypes of colon cancer and subsequently explored prognostic genes with GEPIA2. Enrichment analysis is used by WebGestalt to obtain differential genes. Protein-protein interaction networks of differential genes were constructed using the STRING database a

SUBMITTER: Zhou B 

PROVIDER: S-EPMC9523145 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature